I currently have some code like:
class Bird:
pass
class Swallow(Bird):
__max_airspeed_velocity = 10
def __init__(self, laden):
self.laden = laden
#property
def max_velocity(self):
return self.__max_airspeed_velocity
#property
def current_velocity(self):
if self.laden:
return self.__max_airspeed_velocity / 2
else:
return self.__max_airspeed_velocity
class Parrot(Bird):
__max_in_cage_velocity = 8
def __init__(self, dead):
self.dead = dead
#property
def max_velocity(self):
return self.__max_in_cage_velocity
#property
def current_velocity(self):
if self.dead:
return 0
else:
return self.__max_in_cage_velocity
swallow = Swallow(True)
parrot = Parrot(False)
# Direct variable access is fine
swallow.__max_airspeed_velocity # 10
Swallow.__max_airspeed_velocity # 10
# Getter only works on instance. I see that it references "self", but it only looks at a class variable.
# In practice, this is an obvious reason why it doesn't work. But in theory there should still be a way?
swallow.max_velocity # 10
Swallow.max_velocity # Error
Now let's say I wanted a function that compared birds. I sometimes want to ask about theoretical birds (the classes), and sometimes actual birds (instances).
def compare_max_velocity(bird1, bird2):
return bird1.max_velocity > bird2.max_velocity # only works on instances
compare_max_velocity(Swallow, Parrot) # can I do this using built-ins?
compare_max_velocity(swallow, parrot) # easy
Can I write this function using getters? Do I have to resort to making my own get_max_velocity() function (or direct variable access)?
I'm trying to understand Polymorphism in OOP, i've built a monster parent class, from this main class you can inherit oarcs, wizards and giants..but the main attack method is coded in the parent monster class, and have only a string that is put in a variable name basic_attack
The problem is when i call this attack variable in oarcs, wizards or giants in the child classes, i get this error Instance of 'oarc' has no 'basic_attack' memberpylint(no-member)
please go easy on me and feel free to review my code below.
class monster:
def __init__(self, damage, speed, skill):
self.damage = damage
self.speed = speed
self.skill = skill
def attack(self):
basic_attack = "you've been attacked by "
return basic_attack
class oarc(monster):
def __init__(self, damage, speed, skill, oarc_data):
super().__init__(damage, speed, skill)
self.oarc_data = oarc_data
def attack(self):
return self.basic_attack + self.oarc_data
class wizard(monster):
def __init__(self, damage, speed, skill, wizard_data):
super().__init__(damage, speed, skill)
self.wizard_data = wizard_data
def attack(self):
return self.basic_attack + self.wizard_data
class giant(monster):
def __init__(self, damage, speed, skill, giant_data):
super().__init__(damage, speed, skill)
self.giant_data = giant_data
def attack(self):
return self.basic_attack + self.giant_data
oarc_object = oarc(56, 150, 'ugly', 'Oarc')
wizard_object = wizard(20, 100, 'fast', 'Wizard')
giant_object = giant(100, 20, 'strong', 'Giant')
list = [oarc_object, wizard_object, giant_object]
for each in list:
print(each.attack)
print(oarc_object.attack())
Ok, basically looks like self.basic_attack is never set. Could probably fix with self.basic_attack = basic_attack in def __init__() of class Monster.
The basic_attack = "you've been attacked by " under def attack() in class Monster is not the same as setting basic_attack. That basic_attack is constrained to the attack() function.
For example, let's abstract at non-OOP code;
# define a
a = 0
def test():
# define out
a = 2
# output out
return a
print(test())
>> 2
print(a)
>> 0
Now, if we did not redefine a in test():
# set a
a = 0
# define test
def test():
return a
print(test())
>> 0
print(a)
>> 0
Now if a was only defined within test();
# define test
def test():
# set a
a = 2
# output
return a
print(test())
>> 2
print(a)
>> NameError: name 'a' is not defined
Here's a short Intro to OOP in Python;
Quick & easy; Object-oriented Programming from the ground up with Examples from Pikachu and Bay Area Rapid Transit (BART)
And here's a bit more in-depth application of OOP to post to LinkedIn;
LinkedOut
As I've subclassed QSortFilterModel to be able to search thru several coloumns in a QListView, the CaseInsensitive option no longer works. Ive tried to apply it as follows:
class CustomSortFilterProxyModel(QtCore.QSortFilterProxyModel):
def __init__(self, parent=None):
super(CustomSortFilterProxyModel, self).__init__(parent)
self.filterString = ''
self.filterFunctions = {}
self.setFilterCaseSensitivity(QtCore.Qt.CaseInsensitive) #Applied here
def setFilterString(self, text):
self.filterString = str(text)
self.setFilterCaseSensitivity(QtCore.Qt.CaseInsensitive) #And applied here
self.invalidateFilter()
def filterAcceptsRow(self, row_num, parent):
self.filterColumns = [1,3]
model = self.sourceModel()
row = model.row(row_num)
tests = [self.filterString in row[col] for col in self.filterColumns]
return True in tests
How come my search string is case sensitive?
The sensitivity you set there only applies to the default filterAcceptsRow implementation. If you override it, you'll need to handle this yourself, by doing something like:
return any(self.filterString.casefold() in row[col].casefold() for col in self.filterColumns))
(see the str.casefold docs)
I came up with the following code to decorate instance methods using a decorator that requires the instance itself as an argument:
from functools import wraps
def logging_decorator(tricky_instance):
def wrapper(fn):
#wraps(fn)
def wrapped(*a, **kw):
if tricky_instance.log:
print("Calling %s.." % fn.__name__)
return fn(*a, **kw)
return wrapped
return wrapper
class Tricky(object):
def __init__(self, log):
self.log = log
self.say_hi = logging_decorator(self)(self.say_hi)
def say_hi(self):
print("Hello, world!")
i1 = Tricky(log=True)
i2 = Tricky(log=False)
i1.say_hi()
i2.say_hi()
This seems to work great, but I fear that I may have overlooked some unintended side effects of this trick. Am I about to shoot myself in the foot, or is this safe?
Note that I don't actually want to use this for logging, it's just the shortest meaningful example I could come up with.
It's not really clear to me why you would ever want to do this. If you want to assign a new method type dynamically use types:
import types
class Tricky(object):
def __init__(self):
def method(self):
print('Hello')
self.method = types.MethodType(method, self)
If you want to do something with the instance, do it in the __init__ method. If you just want access to the method's instance inside the decorator, you can use the im_self attribute:
def decorator(tricky_instance):
def wrapper(meth):
print(meth.im_self == tricky_instance)
return meth
return wrapper
Personally, I think this is veering into Maybe-I-Shouldn't-Use-Decorators land.
I think I was trying to be needlessly smart. There seems to be an embarrassingly simpler solution:
from functools import wraps
def logging_decorator(fn):
#wraps(fn)
def wrapped(self, *a, **kw):
if self.log:
print("Calling %s.." % fn.__name__)
return fn(self, *a, **kw)
return wrapped
class Tricky(object):
def __init__(self, log):
self.log = log
#logging_decorator
def say_hi(self):
print("Hello, world!")
i1 = Tricky(log=True)
i2 = Tricky(log=False)
i1.say_hi()
i2.say_hi()
("variables" here refers to "names", I think, not completely sure about the definition pythonistas use)
I have an object and some methods. These methods all need and all change the object's variables. How can I, in the most pythonic and in the best, respecting the techniques of OOP, way achieve to have the object variables used by the methods but also keep their original values for the other methods?
Should I copy the object everytime a method is called? Should I save the original values and have a reset() method to reset them everytime a method needs them? Or is there an even better way?
EDIT: I was asked for pseudocode. Since I am more interested in understanding the concept rather than just specifically solving the problem I am encountering I am going to try give an example:
class Player():
games = 0
points = 0
fouls = 0
rebounds = 0
assists = 0
turnovers = 0
steals = 0
def playCupGame(self):
# simulates a game and then assigns values to the variables, accordingly
self.points = K #just an example
def playLeagueGame(self):
# simulates a game and then assigns values to the variables, accordingly
self.points = Z #just an example
self.rebounds = W #example again
def playTrainingGame(self):
# simulates a game and then assigns values to the variables, accordingly
self.points = X #just an example
self.rebounds = Y #example again
The above is my class for a Player object (for the example assume he is a basketball one). This object has three different methods that all assign values to the players' statistics.
So, let's say the team has two league games and then a cup game. I'd have to make these calls:
p.playLeagueGame()
p.playLeagueGame()
p.playCupGame()
It's obvious that when the second and the third calls are made, the previously changed statistics of the player need to be reset. For that, I can either write a reset method that sets all the variables back to 0, or copy the object for every call I make. Or do something completely different.
That's where my question lays, what's the best approach, python and oop wise?
UPDATE: I am suspicious that I have superovercomplicated this and I can easily solve my problem by using local variables in the functions. However, what happens if I have a function inside another function, can I use locals of the outer one inside the inner one?
Not sure if it's "Pythonic" enough, but you can define a "resettable" decorator
for the __init__ method that creates a copy the object's __dict__ and adds a reset() method that switches the current __dict__ to the original one.
Edit - Here's an example implementation:
def resettable(f):
import copy
def __init_and_copy__(self, *args, **kwargs):
f(self, *args)
self.__original_dict__ = copy.deepcopy(self.__dict__)
def reset(o = self):
o.__dict__ = o.__original_dict__
self.reset = reset
return __init_and_copy__
class Point(object):
#resettable
def __init__(self, x, y):
self.x = x
self.y = y
def __str__(self):
return "%d %d" % (self.x, self.y)
class LabeledPoint(Point):
#resettable
def __init__(self, x, y, label):
self.x = x
self.y = y
self.label = label
def __str__(self):
return "%d %d (%s)" % (self.x, self.y, self.label)
p = Point(1, 2)
print p # 1 2
p.x = 15
p.y = 25
print p # 15 25
p.reset()
print p # 1 2
p2 = LabeledPoint(1, 2, "Test")
print p2 # 1 2 (Test)
p2.x = 3
p2.label = "Test2"
print p2 # 3 2 (Test2)
p2.reset()
print p2 # 1 2 (Test)
Edit2: Added a test with inheritance
I'm not sure about "pythonic", but why not just create a reset method in your object that does whatever resetting is required? Call this method as part of your __init__ so you're not duplicating the data (ie: always (re)initialize it in one place -- the reset method)
I would create a default dict as a data member with all of the default values, then do __dict__.update(self.default) during __init__ and then again at some later point to pull all the values back.
More generally, you can use a __setattr__ hook to keep track of every variable that has been changed and later use that data to reset them.
Sounds like you want to know if your class should be an immutable object. The idea is that, once created, an immutable object can't/should't/would't be changed.
On Python, built-in types like int or tuple instances are immutable, enforced by the language:
>>> a=(1, 2, 3, 1, 2, 3)
>>> a[0] = 9
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: 'tuple' object does not support item assignment
As another example, every time you add two integers a new instance is created:
>>> a=5000
>>> b=7000
>>> d=a+b
>>> d
12000
>>> id(d)
42882584
>>> d=a+b
>>> id(d)
42215680
The id() function returns the address of the int object 12000. And every time we add a+b a new 12000 object instance is created.
User defined immutable classes must be enforced manually, or simply done as a convention with a source code comment:
class X(object):
"""Immutable class. Don't change instance variables values!"""
def __init__(self, *args):
self._some_internal_value = ...
def some_operation(self, arg0):
new_instance = X(arg0 + ...)
new_instance._some_internal_operation(self._some_internal_value, 42)
return new_instance
def _some_internal_operation(self, a, b):
"""..."""
Either way, it's OK to create a new instance for every operation.
See the Memento Design Pattern if you want to restore previous state, or the Proxy Design Pattern if you want the object to seem pristine, as if just created. In any case, you need to put something between what's referenced, and it's state.
Please comment if you need some code, though I'm sure you'll find plenty on the web if you use the design pattern names as keywords.
# The Memento design pattern
class Scores(object):
...
class Player(object):
def __init__(self,...):
...
self.scores = None
self.history = []
self.reset()
def reset(self):
if (self.scores):
self.history.append(self.scores)
self.scores = Scores()
It sounds like overall your design needs some reworking. What about a PlayerGameStatistics class that would keep track of all that, and either a Player or a Game would hold a collection of these objects?
Also the code you show is a good start, but could you show more code that interacts with the Player class? I'm just having a hard time seeing why a single Player object should have PlayXGame methods -- does a single Player not interact with other Players when playing a game, or why does a specific Player play the game?
A simple reset method (called in __init__ and re-called when necessary) makes a lot of sense. But here's a solution that I think is interesting, if a bit over-engineered: create a context manager. I'm curious what people think about this...
from contextlib import contextmanager
#contextmanager
def resetting(resettable):
try:
resettable.setdef()
yield resettable
finally:
resettable.reset()
class Resetter(object):
def __init__(self, foo=5, bar=6):
self.foo = foo
self.bar = bar
def setdef(self):
self._foo = self.foo
self._bar = self.bar
def reset(self):
self.foo = self._foo
self.bar = self._bar
def method(self):
with resetting(self):
self.foo += self.bar
print self.foo
r = Resetter()
r.method() # prints 11
r.method() # still prints 11
To over-over-engineer, you could then create a #resetme decorator
def resetme(f):
def rf(self, *args, **kwargs):
with resetting(self):
f(self, *args, **kwargs)
return rf
So that instead of having to explicitly use with you could just use the decorator:
#resetme
def method(self):
self.foo += self.bar
print self.foo
I liked (and tried) the top answer from PaoloVictor. However, I found that it "reset" itself, i.e., if you called reset() a 2nd time it would throw an exception.
I found that it worked repeatably with the following implementation
def resettable(f):
import copy
def __init_and_copy__(self, *args, **kwargs):
f(self, *args, **kwargs)
def reset(o = self):
o.__dict__ = o.__original_dict__
o.__original_dict__ = copy.deepcopy(self.__dict__)
self.reset = reset
self.__original_dict__ = copy.deepcopy(self.__dict__)
return __init_and_copy__
It sounds to me like you need to rework your model to at least include a separate "PlayerGameStats" class.
Something along the lines of:
PlayerGameStats = collections.namedtuple("points fouls rebounds assists turnovers steals")
class Player():
def __init__(self):
self.cup_games = []
self.league_games = []
self.training_games = []
def playCupGame(self):
# simulates a game and then assigns values to the variables, accordingly
stats = PlayerGameStats(points, fouls, rebounds, assists, turnovers, steals)
self.cup_games.append(stats)
def playLeagueGame(self):
# simulates a game and then assigns values to the variables, accordingly
stats = PlayerGameStats(points, fouls, rebounds, assists, turnovers, steals)
self.league_games.append(stats)
def playTrainingGame(self):
# simulates a game and then assigns values to the variables, accordingly
stats = PlayerGameStats(points, fouls, rebounds, assists, turnovers, steals)
self.training_games.append(stats)
And to answer the question in your edit, yes nested functions can see variables stored in outer scopes. You can read more about that in the tutorial: http://docs.python.org/tutorial/classes.html#python-scopes-and-namespaces
thanks for the nice input, as I had kind of a similar problem. I'm solving it with a hook on the init method, since I'd like to be able to reset to whatever initial state an object had. Here's my code:
import copy
_tool_init_states = {}
def wrap_init(init_func):
def init_hook(inst, *args, **kws):
if inst not in _tool_init_states:
# if there is a class hierarchy, only the outer scope does work
_tool_init_states[inst] = None
res = init_func(inst, *args, **kws)
_tool_init_states[inst] = copy.deepcopy(inst.__dict__)
return res
else:
return init_func(inst, *args, **kws)
return init_hook
def reset(inst):
inst.__dict__.clear()
inst.__dict__.update(
copy.deepcopy(_tool_init_states[inst])
)
class _Resettable(type):
"""Wraps __init__ to store object _after_ init."""
def __new__(mcs, *more):
mcs = super(_Resetable, mcs).__new__(mcs, *more)
mcs.__init__ = wrap_init(mcs.__init__)
mcs.reset = reset
return mcs
class MyResettableClass(object):
__metaclass__ = Resettable
def __init__(self):
self.do_whatever = "you want,"
self.it_will_be = "resetted by calling reset()"
To update the initial state, you could build some method like reset(...) that writes data into _tool_init_states. I hope this helps somebody. If this is possible without a metaclass, please let me know.